Subnational governance for the low carbon energy transition: Mapping the UK’s ‘Energy Constitution’
Bibliographic record
Abstract
The UK has a ‘national’ strategy to decarbonise its energy sector, yet the transfer of key responsibilities to its Devolved Administrations has meant that they control many of the powers that determine the rate and extent of the decarbonisation process. This reflects an asymmetrical distribution of legal responsibilities that has cast a complex range of powers ‘downward’ from the national sphere to subnational scales and which plays a crucial role in shaping the agency at different levels of the UK’s energy governance. This paper provides a detailed exploration of the UK’s ‘Energy Constitution’ as a means of examining the way in which the complex legal framework of devolution shapes the spatial organisation of the UK’s low carbon transition. Previous research on the low carbon transition has remained largely ‘lawless’ and as such has tended to overlook how the legal regimes governing energy both produce space and are shaped by its geographic context. The paper therefore develops a more nuanced understanding of the spatiality, territorialisation and scaling of UK energy governance to highlight a nexus of ambiguity and partial power allocation distributed across a plurality of overlapping ‘legal’ jurisdictions. This raises fundamental questions over how UK constitutional arrangements reify the territoriality of energy governance and structure the relationships between national and subnational multi-level decarbonisation processes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".